Simulated Azure IoT Edge device (such as a PC): Set up Azure IoT Edge ( instructions on Windows, instructions on Linux) and use the amd64 tags. Raspberry Pi 3: Set up Azure IoT Edge on a Raspberry Pi 3 ( instructions to set up the hardware - use raspbian 9 (stretch) or above) + instructions to install Azure IoT Edge) with a SenseHat and use the arm32v7 tags. You can run this solution on either of the following hardware: It has been ported to the newer IoT Edge GA bits.Ĭheck out this video to see this demo in action and understand how it was built: This sample can also be deployed on an 圆4 machine (aka your PC). while keeping your video footage private, lowering your bandwidth costs and even running offline. You can thus add meaning to your video streams to detect road traffic conditions, estimate wait lines, find parking spots, etc. IoT Edge gives you the possibility to run this model next to your cameras, where the video data is being generated. Custom Vision is an image classifier that is trained in the cloud with your own images. This is a sample showing how to deploy a Custom Vision model to a Raspberry Pi 3 device running Azure IoT Edge.
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